Skip to content
llm-speed
Leaderboard/hardware/m3-pro-18-core-gpu

M3 Pro 18-core GPU (reported) LLM benchmark

On the M3 Pro 18-core GPU (reported), single-user chat decode speeds by model size (one result per model) are: ~7–9B models at 22.0 tok/s (mlx; community results only: middle of 3 community results, not measured by llm-speed, source run, community), ~14B models (too few results: 2 models, 0 by llm-speed, 2 community; no middle value) and ~32B models (too few results: 2 models, 0 by llm-speed, 2 community; no middle value). Short-chat workload, local runtimes, dense models only. Each model counts once (its standard run at default context), cold-load rows are left out, and a size class needs results from at least 3 models for a middle value. Quantization, backend and settings vary between submissions, so check each row in the tables below.

Fastest single result in these submissions (any model size)

286.5 decode tok/s

Qwen2.5-0.5B-Instruct-4bit (0.5B) via mlx (4bit). Workload: chat-short. Reported hardware: M3 Pro (18-core GPU) + 36GB unified. see full run

Qwen3-32B-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-shortnot supplied
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.3-7.16tok/s25.65tok/s4,288msr_pnrrpcdqfo4

Qwen2.5-32B-Instruct-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-shortnot supplied
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.3-7.05tok/s33.41tok/s3,921msr_f4x3xaan2ay

gemma-2-9b-it-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-shortnot supplied
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.3-21.97tok/s102.5tok/s1,151msr_q7t7b7dcuz5

Qwen2.5-14B-Instruct-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-short14B
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.34bit14.41tok/s117.9tok/s1,111msr_ia73dzeue0b

phi-4-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-shortnot supplied
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.3-15.61tok/s120.7tok/s936msr_-w8hnn61va_

Llama-3.1-8B-Instruct-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-shortnot supplied
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.3-29.20tok/s203.3tok/s669msr_h0-use1ypnb

Qwen2.5-7B-Instruct-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-short7B
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.34bit30.52tok/s161.9tok/s809msr_llzv_g-ymaf
chat-short7B
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.34bit15.67tok/s54.34tok/s2,411msr_e3t93rscswq

Qwen2.5-0.5B-Instruct-4bit

WorkloadModel sizeReported hardwareBackendQuantdecode tok/sprefill tok/sTTFTRun
chat-short0.5B
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.34bit286.5tok/s656.2tok/s200msr_akcbpx5vcqa
chat-short0.5B
M3 Pro (18-core GPU) + 36GB unified
mlx@0.31.34bit282.6tok/s668.8tok/s196msr_bftqtkilvoe

Models measured on M3 Pro 18-core GPU (reported)